58 research outputs found

    The Variations of Satellite-Based Ecosystem Water Use and Carbon Use Efficiency and Their Linkages with Climate and Human Drivers in the Songnen Plain, China

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    Ecosystem water use efficiency (WUE) and carbon use efficiency (CUE), as two of the most important ecological indicators of an ecosystem, represent the carbon assimilation rate of unit water consumption and the capacity of transferring carbon from the atmosphere to potential carbon sinks. Revealing WUE and CUE changes and their impact factors is vital for regional carbon-water interactions and carbon budget assessment. Climate affects carbon and water processes differently. Compared to WUE, the variations in CUE in response to climate factors and human activity remain inadequately understood. In this study, ecosystem-level WUE and CUE variations in the Songnen Plain (SNP), Northeast China, during 2001–2015, were investigated using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. The relationships between WUE, CUE, main climate factors, and human impacts were explored. The results showed that ecosystem WUE and CUE have fluctuated over time, with regional average values of 1.319 gC·kg−1H2O and 0.516, respectively. Deciduous broad-leaved forests had the highest average WUE but the lowest CUE. The multiyear average CUE of grassland ranked in first place, while the lowest WUE indicated that a lesser capacity of net productivity was generated by the use of limited water supply. WUE and CUE showed a downward trend in most areas of the SNP, indicating that the carbon sequestration capacity of the terrestrial ecosystem became weaker in the past 15 years. Annual precipitation and relative humidity had positive influences on WUE and CUE in more than 60% of the study area. The total annual sunshine duration and annual average temperature negatively affected WUE and CUE in most areas. Human activities had a positive effect on ecosystem WUE changes in the SNP but might inhibit CUE variations. Our findings aid in understanding the biological regulation mechanisms of carbon-water cycle coupling and provide a scientific basis for formulating sustainable regional development strategies and guiding water and land resources management.</jats:p

    Water use efficiency of China\u27s terrestrial ecosystems and responses to drought

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    Water use efficiency (WUE) measures the trade-off between carbon gain and water loss of terrestrial ecosystems, and better understanding its dynamics and controlling factors is essential for predicting ecosystem responses to climate change. We assessed the magnitude, spatial patterns, and trends of WUE of China’s terrestrial ecosystems and its responses to drought using a process-based ecosystem model. During the period from 2000 to 2011, the national average annual WUE (net primary productivity (NPP)/evapotranspiration (ET)) of China was 0.79 g C kg−1 H2O. Annual WUE decreased in the southern regions because of the decrease in NPP and the increase in ET and increased in most northern regions mainly because of the increase in NPP. Droughts usually increased annual WUE in Northeast China and central Inner Mongolia but decreased annual WUE in central China. “Turning-points” were observed for southern China where moderate and extreme droughts reduced annual WUE and severe drought slightly increased annual WUE. The cumulative lagged effect of drought on monthly WUE varied by region. Our findings have implications for ecosystem management and climate policy making. WUE is expected to continue to change under future climate change particularly as drought is projected to increase in both frequency and severity

    Construction and progress of Chinese terrestrial ecosystem carbon, nitrogen and water fluxes coordinated observation

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    Heterogeneous responses of wetland vegetation to climate change in the Amur River basin characterized by normalized difference vegetation index from 1982 to 2020

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    Climate change affects wetland vegetation dramatically in mid- and high- latitudes, especially in the Amur River basin (ARB), straddling three countries and distributing abundance wetlands. In this study, spatiotemporal changes in average normalized difference vegetation index (NDVI) of wetland during the annual growing season were examined in the ARB from 1982 to 2020, and the responses of wetland vegetation to climatic change (temperature and precipitation) in different countries, geographic gradients, and time periods were analyzed by correlation analysis. The NDVI of wetland in the ARB increased significantly (p &lt; 0.01) at the rate of 0.023 per decade from 1982 to 2020, and the NDVI on the Russian side (0.03 per decade) increased faster than that on the Chinese side (0.02 per decade). The NDVI of wetland was significantly positively correlated with daily mean temperature (p &lt; 0.05, r = 0.701) and negatively correlated with precipitation, although the correlation was not significant (p &gt; 0.05, r = −0.12). However, the asymmetric effects of diurnal warming on wetland vegetation were weak in the ARB. Correlations between the NDVI of wetland and climatic factors were zonal in latitudinal and longitudinal directions, and 49°N and 130°E were the points for a shift between increasing and decreasing correlation coefficients, closely related to the climatic zone. Under climate warming scenarios, the NDVI of wetland is predicted to continue to increase until 2080. The findings of this study are expected to deepen the understanding on response of wetland ecosystem to global change and promote regional wetland ecological protection

    Remote Sensing Applications in Monitoring of Protected Areas

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    Protected areas (PAs) have been established worldwide for achieving long-term goals in the conservation of nature with the associated ecosystem services and cultural values. Globally, 15% of the world’s terrestrial lands and inland waters, excluding Antarctica, are designated as PAs. About 4.12% of the global ocean and 10.2% of coastal and marine areas under national jurisdiction are set as marine protected areas (MPAs). Protected lands and waters serve as the fundamental building blocks of virtually all national and international conservation strategies, supported by governments and international institutions. Some of the PAs are the only places that contain undisturbed landscape, seascape and ecosystems on the planet Earth. With intensified impacts from climate and environmental change, PAs have become more important to serve as indicators of ecosystem status and functions. Earth’s remaining wilderness areas are becoming increasingly important buffers against changing conditions. The development of remote sensing platforms and sensors and the improvement in science and technology provide crucial support for the monitoring and management of PAs across the world. In this editorial paper, we reviewed research developments using state-of-the-art remote sensing technologies, discussed the challenges of remote sensing applications in the inventory, monitoring, management and governance of PAs and summarized the highlights of the articles published in this Special Issue

    Remote Sensing of Land Surface Phenology

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    Land surface phenology (LSP) uses remote sensing to monitor seasonal dynamics in vegetated land surfaces and retrieve phenological metrics (transition dates, rate of change, annual integrals, etc.). LSP has developed rapidly in the last few decades. Both regional and global LSP products have been routinely generated and play prominent roles in modeling crop yield, ecological surveillance, identifying invasive species, modeling the terrestrial biosphere, and assessing impacts on urban and natural ecosystems. Recent advances in field and spaceborne sensor technologies, as well as data fusion techniques, have enabled novel LSP retrieval algorithms that refine retrievals at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. Meanwhile, rigorous assessment of the uncertainties in LSP retrievals is ongoing, and efforts to reduce these uncertainties represent an active research area. Open source software and hardware are in development, and have greatly facilitated the use of LSP metrics by scientists outside the remote sensing community. This reprint covers the latest developments in sensor technologies, LSP retrieval algorithms and validation strategies, and the use of LSP products in a variety of fields. It aims to summarize the ongoing diverse LSP developments and boost discussions on future research prospects

    Using the water quality index (WQI), and the synthetic pollution index (SPI) to evaluate the groundwater quality for drinking purpose in Hailun, China

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    Due to the impact of human agricultural production, climate and environmental changes. The applicability of groundwater for drinking purposes has attracted widespread attention. In order to quantify the hydrochemical characteristics of groundwater in Hailun and evaluate its suitability for assessing water for drinking purposes, 77 shallow groundwater samples and 57 deep groundwater samples were collected and analyzed. The results show that deep groundwater in aquifers in the study area is weakly alkaline, while that in shallow is acidic. The abundance is in the order HCO3 - > Cl- > SO4 2- for anions, and Ca2+> Na+> Mg2+ for cations. Groundwater chemical type were dominated by HCO3 -Ca, HCO3 -Ca‱ Mg, and HCO3 -Ca‱ Na. Correlation analysis (CA) and Durov diagram showed that rock weathering and dissolution, human activities, and the hydraulic connection between shallow and deep water are the main reasons affecting the chemical composition of water in Helen. The analysis of water samples based on the WQI model showed that about 23.37, 23.37, 32.46, 12.98, and 7.79% of the shallow groundwater samples were excellent, good, poor, very poor, and unsuitable for drinking purposes, respectively, and that 61.40, 30.90, 5.26, 1.75, and 1.75% of the deep groundwater samples were excellent, good, poor, very poor, and unsuitable for drinking purposes, respectively. The analysis of groundwater samples based on the SPI model showed that 92.98% of the deep groundwater samples were suitable grade, while that 40.25% of the shallow groundwater samples were suitable grade. The spatial distribution maps of the WQI and SPI show that most of the deep groundwater resources in the study area are clean and suitable for drinking, despite the risks of the shallow groundwater in the north and southwest of the study area
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